Creatinine ratio’s association with HbA1c and Lipid profile parameters

Objectives: This study tries to find the associations of Creatinine ratio (Cr) with HbA1c and lipid profile parameters based on a real dataset. Materials & Methods: A real data set has been considered with 1000 individuals, this data set can be found at https://data.mendeley.com/datasets/wj9rwkp9c2/1. Using statistical joint generalized linear models, the creatinine ratio probabilistic model has been derived. Results: From the fitted Log-normal model, the mean Cr is positively associated with Urea (P=0.0004) and is indifferent to HbA1c (P=0.9299), but it is positively associated with the joint interaction effect (JIE) of HbA1c and Urea, i.e., of HbA1c*Urea (P=0.0197). Mean Cr is indifferent to Chol (P=0.8158), while it is positively associated with the JIE of HbA1c*Chol (P=0.0001). Mean Cr is negatively associated with HDL (P=0.0417), TG (P=0.0045), the JIE of HbA1c*HDL (P<0.0001), and the JIE of HbA1c*TG (P=0.0030). Mean Cr is positively associated with the JIE HDL*Chol (P=0.0003). Mean Cr is indifferent to LDL (P=0.3080), while it is negatively associated with the JIE of Chol and LDL, i.e., of Chol*LDL (P=0.0240). Variance of Cr is positively associated with both the marginal effects BMI (P=0.0185) and Chol (P=0.0092), but it is negatively associated with the JIE of BMI*Chol (P=0.0079). Variance of Cr is positively associated with TG (P=0.0061) and Urea (P<0.0001). Conclusions: On the basis of the above real data set, it is established that creatinine ratio maintains a complex relationship with HbA1c and lipid profile parameters along with their joint interaction effects. KEYWORDS Creatinine ratio (Cr), Hemoglobin A1c (HbA1c), Lipid profile parameters, joint generalized linear models (JGLMs).